Open AccessProceedings Article
Logic programs with classical negation
Michael Gelfond,Vladimir Lifschitz +1 more
- pp 579-597
Reads0
Chats0
About:
This article is published in International Conference on Lightning Protection.The article was published on 1990-05-01 and is currently open access. It has received 602 citations till now. The article focuses on the topics: Negation & Predicate functor logic.read more
Citations
More filters
From deduction to knowledge representation
Michal Vince,Ján Šefránek +1 more
TL;DR: Why deduction is not sufficient for knowledge recovery of programs with commonsense is discussed, and the approach to updates is constructed - a role of assumptions in reasoning, use of fixpoint constructions as a formal tool for building a nonmonotonic semantics and, finally, com- putational aspects of non monotonic reasoning.
Journal Article
Representing defaults and negative information without negation-as-failure
TL;DR: In this paper, a new logic programming approach is proposed in which negation and default inference are independent, orthogonal concepts and negation symbols such as strong negation are also available.
A Knowledge Representation Framework Based on Epistemic Logic
TL;DR: A uniform non-monotonic framework for knowledge representation based on epistemic logic is introduced which is sufficiently general to encompass several non monotonic formalisms, including circumscription, autoepistemic logic, various semantics proposed for logic programs and deductive databases as well as Gelfond’s epistemic specifications.
Book ChapterDOI
Logic Programs with Tests
TL;DR: In this article, the authors extend logic programming to deal with logic programs that include new truth functional connectives called tests, and they extend Stable Model Semantics and Three Valued Stable Models Semantics to give meaning to programs with tests.
Book ChapterDOI
Doctoral Consortium Extended Abstract: Multi-context Systems with Preferences
TL;DR: This research formalizes MCSs with preferences (MCSPs) that allows to integrate preferences into an MCS at the context level and at the MCS level, and proposes novel distributed algorithms to compute their semantics.